Programmable responsive hydrogels inspired by classical conditioning algorithm

Hang Zhang, Hao Zeng, Arri Priimägi, Olli Ikkala

Research output: Contribution to journalArticleScientificpeer-review

50 Citations (Scopus)
32 Downloads (Pure)


Living systems have inspired research on non-biological dynamic materials and systems chemistry to mimic specific complex biological functions. Upon pursuing ever more complex life-inspired non-biological systems, mimicking even the most elementary aspects of learning is a grand challenge. We demonstrate a programmable hydrogel-based model system, whose behaviour is inspired by associative learning, i.e., conditioning, which is among the simplest forms of learning. Algorithmically, associative learning minimally requires responsivity to two different stimuli and a memory element. Herein, nanoparticles form the memory element, where a photoacid-driven pH-change leads to their chain-like assembly with a modified spectral behaviour. On associating selected light irradiation with heating, the gel starts to melt upon the irradiation, originally a neutral stimulus. A logic diagram describes such an evolution of the material response. Coupled chemical reactions drive the system out-of-equilibrium, allowing forgetting and memory recovery. The findings encourage to search non-biological materials towards associative and dynamic properties.

Original languageEnglish
Article number3267
JournalNature Communications
Issue number1
Publication statusPublished - 1 Dec 2019
Publication typeA1 Journal article-refereed

Publication forum classification

  • Publication forum level 3

ASJC Scopus subject areas

  • General Chemistry
  • General Biochemistry,Genetics and Molecular Biology
  • General Physics and Astronomy


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